CN113542167A - Underwater acoustic communication method using polarization code and equalizer - Google Patents

Underwater acoustic communication method using polarization code and equalizer Download PDF

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CN113542167A
CN113542167A CN202110814480.5A CN202110814480A CN113542167A CN 113542167 A CN113542167 A CN 113542167A CN 202110814480 A CN202110814480 A CN 202110814480A CN 113542167 A CN113542167 A CN 113542167A
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equalizer
decoding
steps
equalization
channel
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吴倩倩
刘锋
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Shanghai Maritime University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03891—Spatial equalizers
    • H04L25/03949—Spatial equalizers equalizer selection or adaptation based on feedback
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0056—Systems characterized by the type of code used
    • H04L1/0057—Block codes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0056—Systems characterized by the type of code used
    • H04L1/0061—Error detection codes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/12—Arrangements for detecting or preventing errors in the information received by using return channel
    • H04L1/16—Arrangements for detecting or preventing errors in the information received by using return channel in which the return channel carries supervisory signals, e.g. repetition request signals
    • H04L1/18—Automatic repetition systems, e.g. Van Duuren systems
    • H04L1/1812—Hybrid protocols; Hybrid automatic repeat request [HARQ]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference

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  • Computer Networks & Wireless Communication (AREA)
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  • Cable Transmission Systems, Equalization Of Radio And Reduction Of Echo (AREA)

Abstract

The invention provides an underwater acoustic communication method utilizing a polarization code and an equalizer, which converts an underwater acoustic channel into a Gaussian channel through the equalizer to construct the polarization code and adds an HARQ mechanism to improve the performance of the scheme. The scheme is superior to the result of 5 times of turbo equilibrium iteration in the aspect of bit error rate performance, the decoding complexity is low, the coding structure is simple, and only noise variance information needs to be fed back when a Gaussian approximation method is used for constructing a polarization code receiving end.

Description

Underwater acoustic communication method using polarization code and equalizer
Technical Field
The present invention relates to an underwater communication method using a polar code and an equalizer, and more particularly, to a method for improving system performance using an adaptive decision feedback equalizer based on a minimum bit error rate criterion, coding and decoding of a polar code, and using an HARQ mechanism.
Background
The adaptive decision feedback equalization technology can automatically track the change of the channel characteristics, avoid the complex process of firstly carrying out channel estimation and then matrix inversion, and is suitable for underwater acoustic channels with longer storage length. The system performance can be effectively improved by combining the self-adaptive decision feedback equalizer based on the minimum symbol error rate criterion with the Turbo receiver to carry out iterative decoding, but the decoding complexity of the method is higher as the iteration times are more.
Polar codes are the first channel codes to reach the shannon limit theoretically, with lower coding complexity. Currently available polarization code construction methods for underwater acoustic channels are the monte carlo method and the babbitt parameter boundary method. The Monte Carlo method estimates the reliability of the sub-channels through multiple experiments, is suitable for various channels, but has high complexity and is not suitable for practical use. The babbitt parameter boundary method needs to know the characteristic parameters of the underwater acoustic channel to calculate the initial values of the babbitt parameters, and the method needs to calculate and feed back channel state information and has low accuracy.
Disclosure of Invention
The invention provides an underwater communication method by utilizing a polarization code and an equalizer, which comprises the steps of firstly utilizing the equalizer to convert an underwater acoustic channel into a Gaussian channel, using training data to calculate and feed back noise variance, using a Gaussian approximation method to construct the polarization code by a receiving end according to feedback information, secondly adding an HARQ mechanism, and judging whether to retransmit the training data according to a CRC (cyclic redundancy check) check result to reduce the influence of feedback errors.
Specifically, the invention realizes the method by the following steps:
s1, equalizing the underwater acoustic channel by using an equalizer;
s2, the receiving end calculates and feeds back the noise variance;
s3, constructing a polarization code by a transmitting end;
s4, decoding by a receiving end;
s5, performing CRC check on the decoding result;
s6, judging whether to retransmit according to the check result;
the step S1 includes the steps of:
s1.1, assuming that a channel is unchanged in the process of one-time training and testing, a receiving end uses a self-adaptive decision feedback equalizer based on a minimum bit error rate criterion to perform equalization processing on training data; setting feedforward equalizer coefficient to fkStep size of ufFeedback equalizer coefficient of bkStep size of ub(ii) a The output of the equalizer at time k is:
Figure BDA0003169682420000021
s1.2, the equalizer tap coefficient is automatically adjusted according to the decision result output by equalization, the equalizer coefficient is kept unchanged in the test process after all training data are processed, and the coefficient updating process is expressed as follows:
Figure BDA0003169682420000022
Figure BDA0003169682420000023
Figure BDA0003169682420000024
the step S2 includes the steps of:
s2.1, assuming that the equalizer can well offset intersymbol interference, the decision at the k-th moment of the equalizer is output
Figure BDA0003169682420000025
And transmitting signal skExpressed as:
Figure BDA0003169682420000026
where λ represents the deviation after equalization, ηkIs a residual interference term, and after further eliminating the offset λ, the equalization output can be expressed as:
Figure BDA0003169682420000027
s2.2, the process of the signal passing through the hydroacoustic channel can be regarded as the signal passing through a Gaussian channel, the noise variance σ of which2The time average of the N training data can be used for the estimation, and the calculation process is as follows:
Figure BDA0003169682420000031
Figure BDA0003169682420000032
the step S3 includes the steps of:
s3.1, according to the feedback noise variance, the sending end selects a subchannel with high reliability by using a Gaussian approximation method, and the mean value calculation mode of the subchannel is as follows:
Figure BDA0003169682420000033
Figure BDA0003169682420000034
Figure BDA0003169682420000035
Figure BDA0003169682420000036
the error probability of a polarized subchannel is:
Figure BDA0003169682420000037
s3.2, sequencing according to the error probability of the polarized sub-channels, and selecting the sub-channels with low error probability as information bits; the generator matrix G can be obtained according to the information bitsNThe polar code encoding process is as follows:
Figure BDA0003169682420000038
wherein the content of the first and second substances,
Figure BDA0003169682420000039
and
Figure BDA00031696824200000310
respectively before and after polarization coding, binary random sequence and corresponding cyclic redundancy sequence constitute test data
Figure BDA00031696824200000311
Encoded data
Figure BDA00031696824200000312
Retransmitting by modulation;
the step S4 includes the steps of:
and S4.1, the receiving end performs equalization and decoding operation on the received signal. Setting the width L of a decoding path, and reserving L decoding paths with the maximum possibility by using a CA-SCL decoding algorithm;
the step S5 includes the steps of:
s5.1, sequentially passing the obtained decoding paths through CRC, taking the first decoding path passing the CRC as the decoding result, and if all the paths do not pass the CRC, failing the CRC;
the step S6 includes the steps of:
s6.1, setting the maximum retransmission times, if the verification fails, repeating the steps S1-S6 until the verification passes or the maximum retransmission times limit is reached;
the invention has the beneficial effects that: the coding structure is simple, the polarization code receiving end is constructed by using a Gaussian approximation method, only noise variance information needs to be fed back, and the error rate performance is superior to the result of 5 times of turbo equalization iteration.
Drawings
Fig. 1 is a flow chart of an underwater acoustic communication method using a polarization code and an equalizer according to the present invention.
Fig. 2 is a block diagram of an underwater acoustic communication system of an underwater communication method using a polarization code and an equalizer according to the present invention.
Fig. 3 is a HARQ retransmission process of an underwater communication method using a polarization code and an equalizer according to the present invention.
Fig. 4 is a graph comparing bit error rate performance of an underwater communication method using a polarization code and an equalizer according to the present invention and a method using turbo iterative equalization.
Detailed Description
The invention provides an underwater communication method utilizing a polarization code and an equalizer, the implementation process is shown in figure 1, the coefficient of the equalizer is updated by using training data, and an underwater acoustic channel is regarded as a Gaussian channel through the equalizer; the receiving end calculates and feeds back the noise variance by using the balanced output; the receiving end constructs a polarization code by using a Gaussian approximation method according to the feedback information; the receiving end uses CA-SCL decoding mode to decode; passing the decoding result through cyclic redundancy check; and judging whether to retransmit according to the CRC check result to reduce the influence of the feedback error.
Specifically, the method is realized by the following steps:
s1, equalizing the underwater acoustic channel by using an equalizer;
s2, the receiving end calculates and feeds back the noise variance;
s3, constructing a polarization code by a transmitting end;
s4, decoding by a receiving end;
s5, performing CRC check on the decoding result;
s6, judging whether to retransmit according to the check result;
s7, carrying out error rate performance comparison with turbo iterative equalization;
s1.1, assuming that a channel is unchanged in the process of one-time training and testing, setting the length of training data to be 1024 bits, and setting the length of testing data to be 1024 bits; the receiving end uses a self-adaptive decision feedback equalizer based on the minimum bit error rate criterion to carry out equalization processing on the training data; setting feedforward equalizer coefficient to fkStep size uf0.15, feedback equalizer coefficient bkStep size ub0.25; the output of the equalizer at time k is:
Figure BDA0003169682420000051
s1.2, the equalizer tap coefficient is automatically adjusted according to the decision result output by equalization, the equalizer coefficient is kept unchanged in the test process after all training data are processed, and the coefficient updating process is expressed as follows:
Figure BDA0003169682420000052
Figure BDA0003169682420000053
Figure BDA0003169682420000054
s2.1, assuming that the equalizer can well offset intersymbol interference, the decision at the k-th moment of the equalizer is output
Figure BDA0003169682420000055
And transmitting signal skExpressed as:
Figure BDA0003169682420000056
where λ represents the deviation after equalization, ηkIs a residual interference term, and after further eliminating the offset λ, the equalization output can be expressed as:
Figure BDA0003169682420000061
s2.2, the process of the signal passing through the hydroacoustic channel can be regarded as the signal passing through a Gaussian channel, the noise variance σ of which2The time average of the N training data can be used for the estimation and the calculated noise variance σ2And feeding back to the sending end. Variance of noise σ2The calculation process is as follows:
Figure BDA0003169682420000062
Figure BDA0003169682420000063
s3.1, as shown in fig. 2, the sending end selects a subchannel with high reliability by using a gaussian approximation method according to the feedback noise variance, and the mean value calculation method of the subchannel is as follows:
Figure BDA0003169682420000064
Figure BDA0003169682420000065
Figure BDA0003169682420000066
Figure BDA0003169682420000067
the error probability of a polarized subchannel can be expressed as:
Figure BDA0003169682420000068
s3.2, sequencing according to the error probability of the polarized sub-channels, and selecting the sub-channels with low error probability as information bits; the generator matrix G can be obtained according to the information bitsNThe polar code encoding process is as follows:
Figure BDA0003169682420000069
wherein the content of the first and second substances,
Figure BDA00031696824200000610
and
Figure BDA00031696824200000611
respectively before and after polarization coding, 1008-bit binary random sequence and 16-bit cyclic redundancy sequence are set to form test data
Figure BDA00031696824200000612
To pair
Figure BDA00031696824200000613
Polarization coding is carried out with coding efficiency of 1/2, and the coded data
Figure BDA00031696824200000614
Modulating and then sending into an underwater sound channel;
s4.1, the receiving end carries out equalization, demodulation and decoding operation on the received signal; setting the width L of a decoding path to be 16, and reserving L decoding paths with the maximum possibility by using a CA-SCL decoding algorithm;
and S5.1, sequentially passing the obtained decoding paths through cyclic redundancy check, and taking the first decoding path passing the check as the decoding result.
S6.1, as shown in FIG. 3, setting the maximum retransmission times to be 1 time, if the verification is successful, sending an acknowledgement signal (ACK signal) to the sending end, and ending the transmission process; if the verification fails, a NACK signal is sent to the sending end, the sending end resends the training data, the steps S1-S6 are repeated until the verification passes or the maximum retransmission time limit is reached, and when the retransmission process is finished and the verification of the decoding path is not successful, the decoding path with the maximum possibility is selected as the decoding result to be output;
s7.1, comparing the scheme with a turbo equalization algorithm, wherein the turbo equalization algorithm uses the same equalizer setting and the same training data, the coding mode uses a recursive systematic convolutional code with 1/2 code rate, and the generator polynomial of the coder is G1,G2]＝[5,7]Coded numberThe data is modulated and sent again by the interleaver, the receiving end carries out iterative equalization and decoding on the received data, the updating step length of the equalizer is set as uf＝ubThe number of iterations was set to 5, 0.01; the simulation comparison result is shown in fig. 4, and the invention has faster convergence and lower error rate performance than the turbo iteration for 5 times.

Claims (1)

1. An underwater acoustic communication method using a polar code and an equalizer, comprising the steps of:
s1, equalizing the underwater acoustic channel by using an equalizer;
s2, the receiving end calculates and feeds back the noise variance;
s3, constructing a polarization code by a transmitting end;
s4, decoding by a receiving end;
s5, performing CRC check on the decoding result;
s6, judging whether to retransmit according to the check result;
the step S1 includes the steps of:
s1.1, assuming that a channel is unchanged in the process of one-time training and testing, a receiving end uses a self-adaptive decision feedback equalizer based on a minimum bit error rate criterion to perform equalization processing on training data; setting feedforward equalizer coefficient to fkStep size of ufFeedback equalizer coefficient of bkStep size of ub(ii) a The output of the equalizer at time k is:
Figure FDA0003169682410000011
s1.2, the equalizer tap coefficient is automatically adjusted according to the decision result output by equalization, the equalizer coefficient is kept unchanged in the test process after all training data are processed, and the coefficient updating process is expressed as follows:
Figure FDA0003169682410000012
Figure FDA0003169682410000013
Figure FDA0003169682410000014
the step S2 includes the steps of:
s2.1, assuming that the equalizer can well offset intersymbol interference, the decision at the k-th moment of the equalizer is output
Figure FDA0003169682410000021
And transmitting signal skExpressed as:
Figure FDA0003169682410000022
where λ represents the deviation after equalization, ηkIs a residual interference term, and after further eliminating the offset λ, the equalization output can be expressed as:
Figure FDA0003169682410000023
s2.2, the process of the signal passing through the hydroacoustic channel can be regarded as the signal passing through a Gaussian channel, the noise variance σ of which2The time average of the N training data can be used for the estimation, and the calculation process is as follows:
Figure FDA0003169682410000024
Figure FDA0003169682410000025
the step S3 includes the steps of:
s3.1, according to the feedback noise variance, the sending end selects a subchannel with high reliability by using a Gaussian approximation method, and the mean value calculation mode of the subchannel is as follows:
Figure FDA0003169682410000026
Figure FDA0003169682410000027
Figure FDA0003169682410000028
Figure FDA0003169682410000029
the error probability of a polarized subchannel is:
Figure FDA0003169682410000031
s3.2, sequencing according to the error probability of the polarized sub-channels, and selecting the sub-channels with low error probability as information bits; the generator matrix G can be obtained according to the information bitsNThe polar code encoding process is as follows:
Figure FDA0003169682410000032
wherein the content of the first and second substances,
Figure FDA0003169682410000033
and
Figure FDA0003169682410000034
respectively before and after polarization coding, binary random sequence and corresponding cyclic redundancy sequence constitute test data
Figure FDA0003169682410000035
Encoded data
Figure FDA0003169682410000036
Retransmitting by modulation;
the step S4 includes the steps of:
s4.1, the receiving end carries out equalization and decoding operation on the received signal; setting the width L of a decoding path, and reserving L decoding paths with the maximum possibility by using a CA-SCL decoding algorithm;
the step S5 includes the steps of:
s5.1, sequentially passing the obtained decoding paths through CRC, taking the first decoding path passing the CRC as the decoding result, and if all the paths do not pass the CRC, failing the CRC;
the step S6 includes the steps of:
s6.1, setting the maximum retransmission times, and if the verification fails, repeating the steps S1-S6 until the verification passes or the maximum retransmission times limit is reached.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115276912A (en) * 2022-09-28 2022-11-01 鹏城实验室 Decoding cascade iterative underwater acoustic communication system based on Gauss approximate improved polarization code
CN115296750A (en) * 2022-09-28 2022-11-04 鹏城实验室 Underwater acoustic communication system for constructing polarization code based on Gaussian approximation improvement method
CN115314124A (en) * 2022-09-28 2022-11-08 鹏城实验室 Polar code construction method, system and device

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115276912A (en) * 2022-09-28 2022-11-01 鹏城实验室 Decoding cascade iterative underwater acoustic communication system based on Gauss approximate improved polarization code
CN115296750A (en) * 2022-09-28 2022-11-04 鹏城实验室 Underwater acoustic communication system for constructing polarization code based on Gaussian approximation improvement method
CN115314124A (en) * 2022-09-28 2022-11-08 鹏城实验室 Polar code construction method, system and device
CN115314124B (en) * 2022-09-28 2023-01-10 鹏城实验室 Polar code construction method, system and device
CN115296750B (en) * 2022-09-28 2023-01-17 鹏城实验室 Underwater acoustic communication system for constructing polarization code based on Gaussian approximation improvement method
CN115276912B (en) * 2022-09-28 2023-02-21 鹏城实验室 Decoding cascade iterative underwater acoustic communication system based on Gauss approximate improved polarization code
WO2024067173A1 (en) * 2022-09-28 2024-04-04 鹏城实验室 Decoding cascade iterative underwater acoustic communication system based on gaussian approximation improved polar code

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Application publication date: 20211022